• Energy Research
• MY close
• Applied Energy close

With the privatization and intense competition that characterize the volatile energy sector, the gas turbine industry currently faces new challenges of increasing operational flexibility, reducing operating costs, improving reliability and availability while mitigating the environmental impact. In this complex, changing sector, the gas turbine community could address a set of these challenges by further development of high fidelity, more accurate and computationally efficient engine health assessment, diagnostic and prognostic systems. Recent studies have shown that engine gas-path performance monitoring still remains the cornerstone for making informed decisions in operation and maintenance of gas turbines. This paper offers a systematic review of recently developed engine performance monitoring, diagnostic and prognostic techniques. The inception of performance monitoring and its evolution over time, techniques used to establish a high-quality dataset using engine model performance adaptation, and effects of computationally intelligent techniques on promoting the implementation of engine fault diagnosis are reviewed. Moreover, recent developments in prognostics techniques designed to enhance the maintenance decision-making scheme and main causes of gas turbine performance deterioration are discussed to facilitate the fault identification module. The article aims to organize, evaluate and identify patterns and trends in the literature as well as recognize research gaps and recommend new research areas in the field of gas turbine performance-based monitoring. The presented insightful concepts provide experts, students or novice researchers and decision-makers working in the area of gas turbine engines with the state of the art for performance-based condition monitoring.

Abstract The Bruggeman approximation has widely been used for estimating the effective conductivity and diffusivity of both the catalyst and gas diffusion layers of polymer electrolyte membrane (PEM) fuel cells. This approximation is based on the Bruggeman’s Effective Medium Theory [Bruggeman D. Berechnung verschiedener physikalischer konstanten von heterogenen substanzen. Ann Phys (Leipzig) 1935;24:636–79], which provides empirical correlation for the effective properties of a composite system. Since it is an empirical correlation, a unique correlation based on the Bruggeman approximation does not always hold for the PEM fuel cell effective properties. Rather, the Bruggeman correlation is a cell specific and experiment dependent correlation that depends on structure, phase composition, water saturation, experimental parameters, etc. Further, this correlation needs to be combined with other correlations to estimate the effective diffusivities. In this article, a set of mathematical formulations has been proposed for the effective transport properties in both the catalyst and gas diffusion layers of a PEM fuel cell. The effective conductivity and diffusivity expressions are derived from the mathematical formulations of the Hashin Coated Sphere model [Hashin Z. The elastic moduli of heterogeneous materials. J Appl Mech 1962;29:143–50], which provides an identical mathematical foundation for each of these effective properties rather than an empirical correlation and avoid to use of multiple correlations together. The present model formulations agree well with the results available in literature for the limiting case. Hence, the proposed formulations for the effective transport properties will be a useful estimating tool in the numerical modeling of PEM fuel cells.

Abstract Aviation gasoline contains tetraethyl lead to aid on knocking in spark-ignited aircraft engines. Tetraethyl lead in aviation gasoline is the cause of severe health effects and is considered as human carcinogenic compound. Piston aviation fuels initiative evaluated 245 unleaded fuels, but none could match all the performance regulations of aviation gasoline. In this study, optimisation of the knock-limited performance of 83 leaded/unleaded/blends was carried out. The input parameters were the fuels and engine speed. The output parameters were knock-limited data of brake horsepower, torque, brake mean effective pressure, brake specific fuel consumption and average air-to-fuel ratio. The engine speed was varied at 2350–2700 and the fuels were varied at eighty-three levels. The design matrix was selected based on one factor of response surface methodology which contained 581 experimental runs. Analysis of variance was performed on the models to validate the robustness of the model tested. Engine speed, type of fuel and average air-to-fuel ratio were set to be in range while brake horsepower, torque and brake mean effective pressure were maximised and brake specific fuel consumption was minimised. Confirmation test was carried out to validate the predicted and actual outcomes. Results indicated that when the engine was run with a speed of 2700 RPM, RSM AVGAS 100LL MS gave optimum solution with corresponding brake horsepower, torque, brake mean effective pressure, brake specific fuel consumption and average air-to-fuel ratio values of 292.837 Hp, 777.557 Nm, 1099.521 kPa, 0.271 kg/kW h and 13.044 respectively with a desirability of 0.972. The results indicated future focus of similar research into optimization of mid and low octane unleaded alternatives.

Abstract A general optimization framework for the simultaneous operational planning of utility and production systems is presented with the main purpose of reducing the energy needs and material resources utilization of the overall system. The proposed mathematical model focuses mainly on the utility system and considers for the utility units: (i) unit commitment constraints, (ii) performance degradation and recovery, (iii) different types of cleaning tasks (online or offline, and fixed or flexible time-window), (iv) alternative options for cleaning tasks in terms of associated durations, cleaning resources requirements and costs, and (v) constrained availability of resources for cleaning operations. The optimization function includes the operating costs for utility and production systems, cleaning costs for utility systems, and energy consumption costs. Several case studies are presented in order to highlight the applicability and the significant benefits of the proposed approach. In particular, in comparison with the traditional sequential planning approach for production and utility systems, the proposed integrated approach can achieve considerable reductions in startup/shutdown and cleaning costs, and most importantly in utilities purchases, as it is shown in one of the case studies.

An innovative idea on extracting clean energy from man-made wind resources with micro wind turbine system for power generation is introduced in this paper. This system generates on-site clean energy using a micro wind generation system. A vertical axis wind turbine (VAWT) with an enclosure is mounted above a cooling tower’s exhaust fan to harness the wind energy for producing electricity. The VAWT is positioned at a specific position at the cooling tower outlet to avoid a negative impact on the performance of the cooling tower. The enclosure can act as a safety cover and also enhance the performance of the VAWT. It is designed with several guide-vanes positioned at the up-stream side of the wind turbine to create a venturi effect and guide the wind before it interacts with the turbine blades. Moreover, the enclosure design is comprised of diffuser-plates that can draw more wind and accelerate the flow. Laboratory test conducted on a scaled model shows no measurable difference in the air intake speed and current consumption of the power-driven fan when the turbine was spinning above the cooling tower. Field test on an actual induced-draft cooling tower shows no significant difference on the outlet air speed of the cooling tower. A small difference was observed on the power consumption by the fan motor which is 0.39% higher with the presence of the VAWT. This system is retrofit-able to existing cooling towers and has very high market potential due to abundant cooling towers and other unnatural exhaust air resources globally.

Thermal management system is crucial for a Lithium-ion battery pack as cycle life, driving range of electric vehicle, usable capacity and safety are heavily dependent on the operating temperature. Optimum operating temperature of Lithium-ion battery pack is about 25 oC – 40 oC. Power availability of the battery pack may differ according to the operating temperature. Although air cooling is the simplest and cheapest cooling solution, the cooling capacity is still limited by the low specific heat capacity. This will cause large variation of temperature of cells across the battery pack. In this study, mist cooling is proposed for battery pack thermal management system. Experiments and numerical simulations are conducted to investigate the thermal performance of conventional dry air cooling and mist cooling. Simulation results are then validated with the experimental data. The simulation results show that mist cooling can offer lower and more uniform temperature distribution compared to dry air cooling. Mist cooling with mass flow rate of 5 gs-1 and 3 % mist loading fraction is sufficient to ensure the surface temperature of the battery module maintained to below 40 oC. Therefore, mist cooling is a potential solution for the thermal management system of Lithium-ion battery pack.

Despite the recent changing trend in the energy-mix, coal remains the primary source of energy in India. The coal sector in India is one of the most regulated sectors in the world. Considering both sides of the market, we establish the presence of long-run dynamics among economic growth and carbon-dioxide (CO2) emissions over half a century. Our innovation in this study is to introduce coal rent, a proxy for regulated coal sector in India in explaining CO2 emissions and the growth process. We find coal rent influences CO2 emissions with a feedback effect. Both trade openness and financial development are established to be significant in influencing growth process with a feedback effect. Using the longest available time series data, the study fills the major gap in the literature by incorporating the competitive process of this sector in the demand-supply framework and establish the need for investment in advanced coal technologies and alternative energy sources in breaking regulatory barriers. In this respect, we establish a significant role of trade openness and financial development in maintaining economic growth and implementing carbon abatement policies in future.

Many cities are pursuing the low-carbon practices to reduce CO2 and other environmental emissions. However, it is still unclear which aspects a low-carbon city (LCC) covers and how to quantify and certify its low carbon level. In this paper, an indicator framework for the evaluation of LCC was established from the perspectives of Economic, Energy pattern, Social and Living, Carbon and Environment, Urban mobility, Solid waste, and Water. A comprehensive evaluation method was employed for LCC ranking by using the entropy weighting factor method. The benchmark values for LCC certification were also identified. The framework was applied to 10 global cities to rank their low-carbon levels. The comparison of cities at different levels of economic, social, and environmental development enhances the holistic of the study. The results showed that Stockholm, Vancouver, and Sydney ranked higher than the benchmark value, indicating these cities achieved a high level of low-carbon development. Sao Paulo, London, and Mexico City are still in the slow transition towards LCC. Beijing and New York each has much lower LCC level than the benchmark value due to the poor environmental performance and infrastructure supports caused by intensive human activities. The proposed indicator system serves as a guideline for the standardization of LCC and further identifies the key aspects of low-carbon management for different cities.